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RSS FeedsEnergies, Vol. 13, Pages 827: Biomass-Derived Graphitic Carbon Encapsulated Fe/Fe3C Composite as an Anode Material for High-Performance Lithium Ion Batteries (Energies)

 
 

14 february 2020 16:02:51

 
Energies, Vol. 13, Pages 827: Biomass-Derived Graphitic Carbon Encapsulated Fe/Fe3C Composite as an Anode Material for High-Performance Lithium Ion Batteries (Energies)
 


Lithium ion (Li-ion) batteries have been widely applied to portable electronic devices and hybrid vehicles. In order to further enhance performance, the search for advanced anode materials to meet the growing demand for high-performance Li-ion batteries is significant. Fe3C as an anode material can contribute more capacity than its theoretical one due to the pseudocapacity on the interface. However, the traditional synthetic methods need harsh conditions, such as high temperature and hazardous and expensive chemical precursors. In this study, a graphitic carbon encapsulated Fe/Fe3C (denoted as Fe/Fe3C@GC) composite was synthesized as an anode active material for high-performance lithium ion batteries by a simple and cost-effective approach through co-pyrolysis of biomass and iron precursor. The graphitic carbon shell formed by the carbonization of sawdust can improve the electrical conductivity and accommodate volume expansion during discharging. The porous microstructure of the shell can also provide increased active sites for the redox reactions. The in-situ-formed Fe/Fe3C nanoparticles show pseudocapacitive behavior that increases the capacity. The composite exhibits a high reversible capacity and excellent rate performance. The composite delivered a high initial discharge capacity of 1027 mAh g−1 at 45 mA g−1 and maintained a reversible capacity of 302 mAh g−1 at 200 mA g−1 after 200 cycles. Even at the high current density of 5000 mA g−1, the Fe/Fe3C@GC cell also shows a stable cycling performance. Therefore, Fe/Fe3C@GC composite is considered as one of the potential anode materials for lithium ion batteries.


 
38 viewsCategory: Biophysics, Biotechnology, Physics
 
Energies, Vol. 13, Pages 829: Automatic Coal and Gangue Segmentation Using U-Net Based Fully Convolutional Networks (Energies)
Energies, Vol. 13, Pages 848: Pulsating Flow of CNT-Water Nanofluid Mixed Convection in a Vented Trapezoidal Cavity with an Inner Conductive T-Shaped Object and Magnetic Field Effects (Energies)
 
 
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